Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011

2015 ◽  
Vol 24 (1) ◽  
pp. 103 ◽  
Author(s):  
Jianfeng Li ◽  
Yu Song ◽  
Xin Huang ◽  
Mengmeng Li
Keyword(s):  
Forest Fires ◽  
Mainland China ◽  
Burned Area ◽  
Burned Areas ◽  
North East ◽  
China Forestry ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product ◽  
Regional Forest ◽  
Official Data

Forest burning, which emits large amounts of trace gases and particulate matter into the atmosphere, produces great impacts on air quality and climate change. In this study, the MODIS (Moderate-Resolution Imaging Spectroradiometer) burned area product (MCD45A1) and GlobCover land-cover product were integrated to estimate the forest burned areas in mainland China from 2001 to 2011. The results were compared with the official data from China Forestry Yearbooks and China Forestry Statistical Yearbooks. On the national scale, the MCD45A1 data were comparable with the official data. However, great gaps exist between the MCD45A1-derived provincial and regional forest burned areas and the corresponding values from the Forestry Statistical Yearbooks. In particular, the MCD45A1-derived areas were higher than the Forestry Statistical Yearbooks in north-east China and significantly lower in south-west China. Moreover, it was indicated that the MCD45A1 algorithm was unsuitable for retrieving the burned areas of small forest fires. Nevertheless, the MCD45A1 exhibited excellent performance in retrieving seasonal patterns of forest fire, with high fire occurrence in spring and autumn. On balance, more studies are required to assess and improve the MCD45A1 product and more precise data on forest burned areas in China are urgently needed.

Accuracy and spatiotemporal distribution of fire in the Brazilian biomes from the MODIS burned-area products

2020 ◽  
Vol 29 (10) ◽  
pp. 907 ◽  
Author(s):  
Nickolas Castro Santana ◽  
Osmar Abílio de Carvalho Júnior ◽  
Roberto Arnaldo Trancoso Gomes ◽  
Renato Fontes Guimarães
Keyword(s):  
Confusion Matrix ◽  
Burned Area ◽  
Accuracy Analysis ◽  
Visual Interpretation ◽  
Burned Areas ◽  
Active Fire ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product ◽  
Area Monitoring

The Moderate Resolution Imaging Spectroradiometer (MODIS) products are the most used in burned-area monitoring, on regional and global scales. This research aims to evaluate the accuracy of the MODIS burned-area and active-fire products to describe fire patterns in Brazil in the period 2001–2015. The accuracy analysis, in the year 2015, compared the MODIS products (MCD45/MCD64) and the burned areas extracted by the visual interpretation of the LANDSAT/Operational Land Imager (OLI) images from the confusion matrix. The accuracy analysis of the active-fire products (MOD14/MYD14) in the year 2015 used linear regression. We used the most accurate burned-area product (MCD64), in conjunction with environmental variables of land use and climate. The MCD45 product presented a high error of commission (>36.69%) and omission (>77.04%) for the whole country. The MCD64 product had fewer errors of omission (64.05%) compared with the MCD45 product, but increased errors of commission (45.85%). MCD64 data in 2001–2015 showed three fire domains in Brazil determined by the climatic pattern. Savanna and grassy areas in semi-humid zones are the most prone areas to fire, burning an average of 25% of their total area annually, with a fire return interval of 5–6 years.

scholarly journals Evaluation of short-term changes of hydrological response in mountainous basins of the Vitim Plateau (Russia) after forest fires based on data analysis and hydrological modelling

2015 ◽  
Vol 371 ◽  
pp. 157-162 ◽  
Author(s):  
O. M. Semenova ◽  
L. S. Lebedeva ◽  
N. V. Nesterova ◽  
T. A. Vinogradova
Keyword(s):  
Forest Fires ◽  
Model Performance ◽  
Burned Area ◽  
Model Parameters ◽  
Hydrological Response ◽  
Short Term ◽  
Burnt Area ◽  
Area Product ◽  
Induced Changes ◽  
Fire Impact

Abstract. Twelve mountainous basins of the Vitim Plateau (Eastern Siberia, Russia) with areas ranging from 967 to 18 200 km2 affected by extensive fires in 2003 (from 13 to 78% of burnt area) were delineated based on MODIS Burned Area Product. The studied area is characterized by scarcity of hydrometeorological observations and complex hydrological processes. Combined analysis of monthly series of flow and precipitation was conducted to detect short-term fire impact on hydrological response of the basins. The idea of basin-analogues which have significant correlation of flow with "burnt" watersheds in stationary (pre-fire) period with the assumption that fire impact produced an outlier of established dependence was applied. Available data allowed for qualitative detection of fire-induced changes at two basins from twelve studied. Summer flow at the Amalat and Vitimkan Rivers (22 and 78% proportion of burnt area in 2003, respectively) increased by 40–50% following the fire.The impact of fire on flow from the other basins was not detectable.The hydrological model Hydrograph was applied to simulate runoff formation processes for stationary pre-fire and non-stationary post-fire conditions. It was assumed that landscape properties changed after the fire suggest a flow increase. These changes were used to assess the model parameters which allowed for better model performance in the post-fire period.

scholarly journals Daily black carbon emissions from fires in northern Eurasia for 2002–2015

2016 ◽  
Vol 9 (12) ◽  
pp. 4461-4474 ◽  
Author(s):  
Wei Min Hao ◽  
Alexander Petkov ◽  
Bryce L. Nordgren ◽  
Rachel E. Corley ◽  
Robin P. Silverstein ◽  
...  
Keyword(s):  
Black Carbon ◽  
Carbon Emissions ◽  
Forest Fires ◽  
The Arctic ◽  
Northern Eurasia ◽  
Burned Areas ◽  
International Panel ◽  
Western Asia ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Inventory Survey

Abstract. Black carbon (BC) emitted from fires in northern Eurasia is transported and deposited on ice and snow in the Arctic and can accelerate its melting during certain times of the year. Thus, we developed a high spatial resolution (500 m  ×  500 m) dataset to examine daily BC emissions from fires in this region for 2002–2015. Black carbon emissions were estimated based on MODIS (Moderate Resolution Imaging Spectroradiometer) land cover maps and detected burned areas, the Forest Inventory Survey of the Russian Federation, the International Panel on Climate Change (IPCC) Tier-1 Global Biomass Carbon Map for the year 2000, and vegetation specific BC emission factors. Annual BC emissions from northern Eurasian fires varied greatly, ranging from 0.39 Tg in 2010 to 1.82 Tg in 2015, with an average of 0.71 ± 0.37 Tg from 2002 to 2015. During the 14-year period, BC emissions from forest fires accounted for about two-thirds of the emissions, followed by grassland fires (18 %). Russia dominated the BC emissions from forest fires (92 %) and central and western Asia was the major region for BC emissions from grassland fires (54 %). Overall, Russia contributed 80 % of the total BC emissions from fires in northern Eurasia. Black carbon emissions were the highest in the years 2003, 2008, and 2012. Approximately 58 % of the BC emissions from fires occurred in spring, 31 % in summer, and 10 % in fall. The high emissions in spring also coincide with the most intense period of ice and snow melting in the Arctic.

scholarly journals Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burned area

2013 ◽  
Vol 10 (8) ◽  
pp. 14141-14167 ◽  
Author(s):  
I. N. Fletcher ◽  
L. E. O. C. Aragão ◽  
A. Lima ◽  
Y. Shimabukuro ◽  
P. Friedlingstein
Keyword(s):  
Forest Fires ◽  
Fire Spread ◽  
Burned Area ◽  
Burnt Area ◽  
Pareto Model ◽  
Fractal Properties ◽  
Vegetation Models ◽  
Area Product ◽  
Global Vegetation ◽  
Tapered Pareto

Abstract. Current methods for modelling burnt area in Dynamic Global Vegetation Models involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation. Using observed fractal distributions of fire scars in Brazilian Amazonia, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. Several parameterizations of two possible distributions are calibrated at multiple spatial resolutions using a satellite-derived burned area map, and compared. The tapered Pareto model most accurately simulates the total area burnt (only 3.5 km2 larger than the recorded 16 387 km2) and its spatial distribution. When tested pan-tropically using MODIS MCD14ML fire counts, the model accurately predicts temporal and spatial fire trends, but produces generally higher estimates than the GFED3.1 burnt area product, suggesting higher pan-tropical carbon emissions from fires than previously estimated.

scholarly journals Global analysis of radiative forcing from fire-induced shortwave albedo change

2015 ◽  
Vol 12 (2) ◽  
pp. 557-565 ◽  
Author(s):  
G. López-Saldaña ◽  
I. Bistinas ◽  
J. M. C. Pereira
Keyword(s):  
Land Surface ◽  
Radiative Forcing ◽  
Global Analysis ◽  
Weather Prediction ◽  
Global Scale ◽  
Burned Area ◽  
Albedo Change ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Environmental Prediction ◽  
Area Product

Abstract. Land surface albedo, a key parameter to derive Earth's surface energy balance, is used in the parameterization of numerical weather prediction, climate monitoring and climate change impact assessments. Changes in albedo due to fire have not been fully investigated on a continental and global scale. The main goal of this study, therefore, is to quantify the changes in instantaneous shortwave albedo produced by biomass burning activities and their associated radiative forcing. The study relies on the MODerate-resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned-area product to create an annual composite of areas affected by fire and the MCD43C2 bidirectional reflectance distribution function (BRDF) albedo snow-free product to compute a bihemispherical reflectance time series. The approximate day of burning is used to calculate the instantaneous change in shortwave albedo. Using the corresponding National Centers for Environmental Prediction (NCEP) monthly mean downward solar radiation flux at the surface, the global radiative forcing associated with fire was computed. The analysis reveals a mean decrease in shortwave albedo of −0.014 (1σ = 0.017), causing a mean positive radiative forcing of 3.99 Wm−2 (1σ = 4.89) over the 2002–20012 time period in areas affected by fire. The greatest drop in mean shortwave albedo change occurs in 2002, which corresponds to the highest total area burned (378 Mha) observed in the same year and produces the highest mean radiative forcing (4.5 Wm−2). Africa is the main contributor in terms of burned area, but forests globally give the highest radiative forcing per unit area and thus give detectable changes in shortwave albedo. The global mean radiative forcing for the whole period studied (~0.0275 Wm−2) shows that the contribution of fires to the Earth system is not insignificant.

scholarly journals Fire Activity and Their Relationship with the Global Fire Weather Index Database Components in Guinea

2019 ◽  
Vol 8 (2) ◽  
pp. 18
Author(s):  
Mamadou Baïlo Barry ◽  
Daouda Badiane ◽  
Saïdou Moustapha Sall ◽  
Moussa Diakhaté ◽  
Habib Senghor
Keyword(s):  
Statistical Analysis ◽  
Fire Behavior ◽  
Burned Area ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Burned Areas ◽  
Active Fire ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

The relationships between the Canadian Fire Weather Index (FWI) System components and the monthly burned area as well as the number of active fire which has taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua/TERRA were investigated in 32 Guinean stations between 2003 and 2013. A statistical analysis based on a multi-linear regression model was used to estimate the skills of FWI components on the predictability of burned area and active fire. This statistical analysis gave performances explaining between 16 to 79% of the variance for the burned areas and between 29 and 82% of the variance for the number of fires (P<0.0001) at lag 0. Respectively 16 to 79 % and 29 to 82 % of the variance of the burned areas and variance for the number of fires (P<0.0001) at lag0 can be explained based on the same statistical analysis. All the combinations used gave significant performances to predict the burned areas and active fire on the monthly timescale in all stations excepted Fria and Yomou where the predictability of the burned areas was not obvious. We obtained a significant correlation between the average over all of the stations of burned areas, active fires and FWI composites with percentage of variance between (75 to 84% and 29 to 77%) for active fires and burned areas at lag0 respectively. While for burned area peak (January), the skill of the predictability remains significant only one month in advance, for the active fires, the model remains skilful 1 to 3 months in advance. Results also showed that active fires are more related to fire behavior indices while the burned areas are related to the fine fuel moisture codes. These outcomes have implications for seasonal forecasting of active fire events and burned areas based on FWI components, as significant predictability is found from 1 to 3 months and one month before respectively.

scholarly journals Estimation of Forest Fire Emissions in Southwest China from 2013 to 2017

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 15 ◽  
Author(s):  
Wenjia Wang ◽  
Qixing Zhang ◽  
Jie Luo ◽  
Ranran Zhao ◽  
Yongming Zhang
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Southwest China ◽  
Global Climate ◽  
Pollutant Emissions ◽  
Fire Emissions ◽  
Forest Fire Management ◽  
Emissions Inventories ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Regional Forest

Forest fire emissions have a great impact on local air quality and the global climate. However, the current and detailed regional forest fire emissions inventories remain poorly studied. Here we used Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate monthly emissions from forest fires at a spatial resolution of 500 m × 500 m in southwest China from 2013 to 2017. The spatial and seasonal variations of forest fire emissions were then analyzed at the provincial level. The results showed that the annual average emissions of CO2, CO, CH4, SO2, NH3, NOX, PM, black carbon, organic carbon, and non-methane volatile organic compounds from forest fires were 1423.19 × 103, 91.66 × 103, 4517.08, 881.07, 1545.04, 1268.28, 9838.91, 685.55, 7949.48, and 12,724.04 Mg, respectively. The forest fire emissions characteristics were consistent with the characteristics of forest fires, which show great spatial and temporal diversity. Higher pollutant emissions were concentrated in Yunnan and Tibet, with peak emissions occurring in spring and winter. Our work provides a better understanding of the spatiotemporal representation of regional forest fire emissions and basic data for forest fire management departments and related research on pollution and emissions controls. This method will also provide guidance for other areas to develop high-resolution regional forest fire emissions inventories.

scholarly journals Burned Area Mapping over the Southern Cape Forestry Region, South Africa Using Sentinel Data within GEE Cloud Platform

2021 ◽  
Vol 10 (8) ◽  
pp. 511
Author(s):  
Sifiso Xulu ◽  
Nkanyiso Mbatha ◽  
Kabir Peerbhay
Keyword(s):  
South Africa ◽  
Forest Fires ◽  
Google Earth ◽  
Burned Area ◽  
Western Cape ◽  
Planted Forests ◽  
Poor Countries ◽  
Burned Areas ◽  
Forestry Industry ◽  
High Level

Planted forests in South Africa have been affected by an increasing number of economically damaging fires over the past four decades. They constitute a major threat to the forestry industry and account for over 80% of the country’s commercial timber losses. Forest fires are more frequent and severe during the drier drought conditions that are typical in South Africa. For proper forest management, accurate detection and mapping of burned areas are required, yet the exercise is difficult to perform in the field because of time and expense. Now that ready-to-use satellite data are freely accessible in the cloud-based Google Earth Engine (GEE), in this study, we exploit the Sentinel-2-derived differenced normalized burned ratio (dNBR) to characterize burn severity areas, and also track carbon monoxide (CO) plumes using Sentinel-5 following a wildfire that broke over the southeastern coast of the Western Cape province in late October 2018. The results showed that 37.4% of the area was severely burned, and much of it occurred in forested land in the studied area. This was followed by 24.7% of the area that was burned at a moderate-high level. About 15.9% had moderate-low burned severity, whereas 21.9% was slightly burned. Random forests classifier was adopted to separate burned class from unburned and achieved an overall accuracy of over 97%. The most important variables in the classification included texture, NBR, and the NIR bands. The CO signal sharply increased during fire outbreaks and marked the intensity of black carbon over the affected area. Our study contributes to the understanding of forest fire in the dynamics over the Southern Cape forestry landscape. Furthermore, it also demonstrates the usefulness of Sentinel-5 for monitoring CO. Taken together, the Sentinel satellites and GEE offer an effective tool for mapping fires, even in data-poor countries.

scholarly journals Effects of prescribed forest burning on carabid beetles (Coleoptera: Carabidae): a case study in south-eastern Norway

2006 ◽  
Vol 17 (3) ◽  
Author(s):  
Konstantin Gongalsky ◽  
Fred Midtgaard ◽  
Hans Overgaard
Keyword(s):  
Forest Fires ◽  
Prescribed Burning ◽  
Abundant Species ◽  
Carabid Beetles ◽  
Burned Area ◽  
Burned Areas ◽  
Clear Cut ◽  
Se Norway ◽  
Eastern Norway

The influence of prescribed burning on ground beetles was studied in a single 12 ha stand that was partially clear-cut, selectively-cut and retained (= standing forest), and was compared to an unburned stand in 2002 in SE Norway. Thirty-two species were collected using Barber pitfall traps. Carabids were more numerous and more diverse in the burned area, compared to the unburned forest. Overall abundance was highest in the selectively-cut treatment, followed by the clear-cut and standing forest. Species diversity tended to increase in the sequence unburned forest – burned standing forest – burned selectively-cut – burned clearcut. Species composition differed little between the burned treatments. Pterostichus adstrictus, a species associated with open habitats and which frequently colonizes burned areas, was the most abundant species collected. It was most common in the burned area, particularly in the selectively-cut treatment. Our results suggest that burning of a single stand may support some carabid species, even endangered ones, although larger forest fires are probablymore effective for conservation purposes.

scholarly journals AN UNSUPERVISED METHOD BASED ON FIRE INDEX ENHANCEMENT AND GRNN FOR AUTOMATED BURNED AREA MAPPING FROM SINGLE-PERIOD REMOTE SENSING IMAGERY

2021 ◽  
Vol V-3-2021 ◽  
pp. 37-42
Author(s):  
Q. Zhang ◽  
Y. Xiao
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Current Situation ◽  
General Regression Neural Network ◽  
Burned Area ◽  
Area Index ◽  
Remote Sensing Imagery ◽  
Burned Areas ◽  
Unsupervised Method ◽  
Burned Area Mapping

Abstract. In the current situation of frequent forest fires, the study of forest burned area mapping is important. However, there is still room for improvement in the accuracy of existing forest burning area mapping methods. Therefore, in this paper, an unsupervised method based on fire index enhancement and GRNN (General Regression Neural Network) is proposed for automated forest burned area mapping from single-date post-fire remote sensing imagery. The proposed method first uses adaptive spatial context information to enhance the generated fire index to improve its ability to indicate the burned areas. Then the uncertainty analysis is performed on the enhanced fire index to extract reliable burned samples and non-burned samples for subsequent classifier training. Finally, the improved GRNN model considering the spatial correlation of pixels is used as a classifier to binarize the enhanced fire index to generate the final burned area map. Based on two commonly used fire indexes, NBR (Normalized Burn Ratio) and BAI (Burned Area Index), this paper conducts burned area mapping experiments on a post-fire image of a forest area in Inner Mongolia, China to test the effectiveness of the proposed method, and two commonly used threshold methods (Otsu and Kmeans clustering) are also used to conduct burned area mapping based on threshold segmentation of fire index for comparison experiments. The experimental results prove the effectiveness and superiority of the proposed method. The proposed method is unsupervised and automated, so it has high application value and potential under the current situation of frequent forest fires.

Sign in / Sign up

Export Citation Format

Share Document